Fulfilling the energy demand from the people all over the world would be not enough if the energy sources are only limited to utilization of non-renewable sources such as fuel, gas and coal. Besides, most non-renewable energies cause pollution and less non-environmentally friendly. Hence, renewable energies are introduced in the past two decades to fulfill the energy demand. One of the popular renewable energies is solar energy which is extracted by converting sunlight into electrical **power** using the **photovoltaic** **system**. However, the conversion efficiency is relatively low with the range of only from 12% up to 20%, and it is highly dependent on the solar irradiation and panel temperature [1]. Thus, in this paper, **Maximum** **Power** **Point** **Tracking** (MPPT) control technique is explained which can increase the efficiency of the overall **Photovoltaic** (PV) **system** by extracting the **maximum** available **power** from the PV arrays [1-3].

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The **photovoltaic** **system** is highly affected by the partial shading condition, which is one of the crucial issues in harvesting solar energy. Numerous techniques have been proposed and elaborated extensively by researchers to tackle the partial shading issue, but most of the methods are complex and costly. The obtained simulation results have verified that the proposed technique-a simple checking algorithm for **Perturb** and **Observe** (P&O) **Maximum** **Power** **Point** **Tracking** (MPPT) - can be used under several levels of irradiation effectively. The obtained results from the **system** with the proposed approach are close to the desired output. It gives approximately only 1.75% of error, thus has 98.25% **system** efficiency. On the other hand, the **system** with conventional P&O MPPT seems to be unstable and has higher percentage of error. In short, the proposed technique is a simple and inexpensive method with only addition of a checking algorithm into the P&O MPPT, yet gives a better result for the **system**.

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The most common approach to find MPP is using **Perturb** & **Observe** (P&O) algorithm [13-19]. The technique is simple and requires low cost for implementation. The method operates by detecting the output **power** of the PV array. P&O operates stage by stage for perturbing and compares the output **power** by applying the perturbed voltage to change the operating voltage of the PV array. However, the conventional P&O MPPT has lots of flaws, especially when the sun irradiation is not uniform. This causes inefficiency of the PV **system**. Nevertheless, in this research, P&O algorithm has been used as the MPPT of the **system**, with some adjustments made to increase the efficiency, as will be elaborated in the next section.

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Due to the non-linear characteristics of I–V and P–V curve, the **tracking** of the **maximum** **power** **point** (MPP) at various environmental conditions is a challenging task. The issue becomes more complicated when the entire PV array is subjected to partial shading. In both circumstances (uniform and partial shading), conventional and SC techniques exhibit several limitations that results in dropping the efficiency by a significant margin. However, due to the simplicity in structure and implementation, conventional P&O based MPPT is most widely used in both research and commercial purposes. This research intends to mitigate all the limitations of the conventional P&O approach withstanding the similar simple structure. To achieve that, no additional sensors are used for the implementation. However, based on the critical analysis of the P–V curve under different environmental conditions several relations are utilized to measure irradiance and update open circuit voltage continuously. Besides, an improved scanning technique is developed to ensure the **tracking** of the global peak under partial shading. Thus, few additional lines in coding is sufficient to enable P&O to handle varying irradiance and temperature along with the partial shading. Therefore, the implementation of the proposed MA-P&O ensures the optimum **power** extraction from the PV **system** throughout the operation lifetime.

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The Hill climb search (HCS) MPPT algorithm is also called perturbation and observation (P&O) MPPT algorithm. In **Perturb**-and-**observe** algorithm method, we only use one sensor and hence it is very easy to implement. Voltage sensor used, senses the PV array voltage and so the cost of implementation is less among all other MPPT algorithm. The **Perturb**-and-**observe** algorithm for **maximum** **power** **point** **tracking** is simplest techniques among all the MPPT techniques in literatures. It is based on the simple mathematical condition, i.e. dP/dV = 0, where P and V are **power** and voltage at output of PV module respectively. From fig. 1, it can be seen that increase in voltage increases **power** when the PV array operates in the left of MPP and **power** decreases on increasing voltage when the same is operates in the right of MPP. Hence if dP/dV > 0, the perturbation should be same and if dP/dV < 0, the perturbation should be reversed. The process should be repeated periodically until dP/dV = 0 reached (**maximum** **power** **point**) [1], [3], [4], [7].

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[17]. Dash Soubhagya K, Nema Savita, Nema R K, and Verma Deepak. "A comprehensive assessment of **maximum** **power** **point** **tracking** techniques under uniform and non-uniform irradiance and its impact on **photovoltaic** systems: A **review**." Journal of Renewable and Sustainable Energy 7, no. 6 (2015): 063113. [18]. Verma Deepak, Nema Savita, Shandilya A M and Dash Soubhagya K. "Comprehensive analysis of

coefficients of the PV module and the effects of changing irradiance on the PV. Then the **maximum** **power** is determined by obtaining the I-V curve. The points of the I-V curve are obtained by numerically solving the diode equation. This **maximum** **power** voltage is stored in a lookup table and is the reference voltage for a given irradiance and temperature. The implementation of the offline method shows that the **system** reaches **maximum** **power** quickly and is faster than when incremental conductance is used. This main

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Like in the fractional voltage method, k2 is not constant. It is found to be between 0.78 and 0.92. The accuracy of the method and **tracking** efficiency depends on the accuracy of K2 and periodic measurement of short circuit current. C.Perturb and **Observe**: In P&O method, the MPPT algorithm is based on the calculation of the PV output **power** and the **power** change by sampling both the PV current and voltage. The tracker operates by periodically incrementing or decrementing the solar array voltage. If a given perturbation leads to an increase (decrease) in the output **power** of the PV, then the subsequent perturbation is generated in the same (opposite) direction. So, the duty cycle of the dc chopper is changed and the process is repeated until the **maximum** **power** **point** has been reached. Actually, the **system** oscillates about the MPP. Reducing the perturbation step size can minimize the oscillation. However, small step size slows down the MPPT. To solve this problem, a variable perturbation size that gets smaller towards the MPP. However, the P&O method can fail under rapidly changing atmospheric conditions. Several research activities have been carried out to improve the traditional Hill-climbing and P&O

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Various approaches have been reported to implement MPPT such as **perturb** and **observe** (P&O) method [4-5], the incremental conductance method, constant voltage method and short-circuit current method [6]. Using this method the **maximum** **power** **point** can be found for specified solar irradiation and temperature condition but they display oscillatory behaviour around the **maximum** **power** **point** under normal operating conditions. Moreover the **system** will not respond quickly to rapid changes in temperature or irradiance. On the other hand the conventional PI controllers are fixed- gain feedback controllers. Therefore they cannot compensate the parameter variations in the process and cannot adapt changes in the environment. PI-controlled **system** is less responsive to real and relatively fast alterations in state and so the **system** will be slower to reach the set **point**. Recently

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The FSM model shown in Figure 1.3 is probably the model of a Moore-type FSM. Most commonly FSM are required to generate the combinatorial logic required to implement the next state decoder and the output decoder. But here FSMs discussed in the context of VHDL. The true **power** of VHDL starts to emerge in its dealings with FSMs. the versatility of VHDL behavioral modeling removes the need for large paper designs of endless K-maps and endless combinatorial logic. There are several different approaches used to model FSMs using VHDL. The many different possible approaches are the result of the general versatility of VHDL as a programming language. This section discuses the probability of the clearest approach for FSM implementation. A block diagram of the approach used in the implementation of FSMs is shown in Figure 1.4. The approach used here divides the FSM into two VHDL processes. One process, referred to as the Synchronous Process, handles all the matters regarding clocking and other controls associated with the storage element. The other process, the Combinatorial handles all the matters associated with the Next State Decoder and the Output Decoder of Figure 1.3. Note that the two blocks in Figure 1.3 are both comprised of solely of combinatorial logic. There is some new lingo used in the description of signals used in Figure 1.4 this description is outlined and described below:

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Abstract: **Photovoltaic** **system** is growing rapidly in today's world. In the recent trend PV industries are gaining more importance but due to its dependence on several factors the actual **power** supplied from the PV to the load is not sufficient. Thus in order to make full utilization of PV **system** effective **tracking** is very necessary. In this paper an improved detail MPPT technique is demonstrated. The duty cycles obtained from this method are analyzed to get a better duty ratio so that the **system** can operate at peak **power** **point** irrespective of any load condition. The detailed work is carried out in MATLAB for resistive load. Therefore MPPT controller with DC-DC converter is considered to carry out effective load matching and make the PV **system** operate at MPP **point**. There are various MPPT methods for PV **system** using soft computing techniques. The results found in this work shows that the PV standalone **system** using the improved MPPT technique give better performance and higher efficiency i.e 98.88% in comparison to other existing methods.

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According to the basic theory of fuzzy PID controller, the controlling simulation programmer is compiled by MATLAB software, at the same time the traditional PID controller is applied in controlling the same **system**. A chemical **photovoltaic** **power** **system** is used as researching object, the corresponding parameters are listed as follows: short-circuit current I sc is equal to 4.88A, the open circuit voltage V oc is equal to 20.6V, the current of **maximum** **power** **point** I m is equal to 4.18A , the voltage of **maximum** **power** **point** V m is equal to 16.8V.

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Solar energy can play an important role in solving the energy problems in those countries lie in the Sun Belt. **Photovoltaic** (PV) energy is one of the useful applications for solar energy. For any PV module, both current and voltage vary proportionally to the load and the solar radiation level as a nonlinear relation, which causes the continuous variation of the **maximum** **power** **point** (MPP). Since the **maximum** **power** for a certain load can be taken from the PV module at a distinct **point** for each radiation level, **maximum** **power** **point** **tracking** (MPPT) can be used to follow the optimum operating **point**. This paper presents design and build a simple MPPT based on **perturb** and **observe** technique for a small DC load driven by a PV module. The experimental results showed that using the proposed MPPT promotes a good matching between the PV module and its load. According to the good matching, the daily output energy can be increased by about 37-42% more than that of the direct coupling between the load and the PV module.

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There is only one **point** for each photoelectric panel called MPP located on the voltage-current (I-V) curve. At this **point**, the PV **system** works at **maximum** efficiency with **maximum** output **power**. Although this **point** is important, MPP is only known when using MPP algorithms. The hatch **point** must be traced to the practical **point** of the PV array. Access to a MPP **point** is done by using direct and indirect methods. Known methods use **photovoltaic** or current voltage or both and classify these as methods as direct methods. In this way, there is no need to know in advance about the characteristics of a plank plate and here

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Due to the fossil fuel exhaustion and the environmental problems caused by the conventional **power** generation such as gasoline, coal, etc..., renewable energy sources and among them **photovoltaic** panels and wind-generators are now widely used [1]. **Photovoltaic** (PV) energy is one of the most promising renewable energy it is clean, inexhaustible and free to harvest. However, there are two main drawbacks of PV **system**, namely the high installation cost and the low conversion efficiency of PV modules [2]. Besides that, PV characteristics are non linear and it is very much weather dependent. Fig.1 and Fig.2 show the I-V and P-V characteristics of a typical PV module for a series of temperatures and solar irradiance levels [3, 4]. It can be noticed that PV output voltage greatly governed by temperature while PV output current has approximate linear relationship with solar irradiances. In general, there is a unique **point** on the I-V or P-V curve, called the **Maximum** **Power** **Point** (MPP), at which the entire PV **system** (array, converter, etc…) operates with **maximum** efficiency and produces its **maximum** output **power**. However, since the MPP varies with insolation and seasons, it is difficult to maintain MPP operation at all solar insolations without changes in the **system** parameters. To overcome this problem an intermediate DC-DC converter is proposed. The MPP **tracking** is applied to PV systems in order to extract **maximum** available **power** © 2014 Elsevier Ltd. This is an open access article under the CC BY-NC-ND license

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Deepak Verma received BE degree in Electrical & Electronics Engineering from RGTU, Bhopal in 2008. He has completed his M. Tech. and Ph.D. from Maulana Azad National Institute of Technology Bhopal in 2010 and 2016. He is currently working as an Assistant Professor in the Department of Electrical & Electronics Engineering, Birla Institute of Technology Mesra, Jaipur Campus, India. His research interest includes performance optimization of solar PV array and **maximum** **power** **point** **tracking** in solar PV systems. His publications include 8 h-indexed (Thomson Reuter) publications, 7 i10-index publications with more than 300 citations.

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Abstract—**Maximum** **power** **point** **tracking** (MPPT) is used in **photovoltaic** (PV) systems to maximize the PV array output **power**, irrespective of the temperature and irradiation conditions and the load electrical characteristics. This paper presents a practical implementation of perturbation and observation (P&O) and incremental conductance (IncCon) algorithms based on PIC18F452 microcontroller for **tracking** of the **maximum** **power** generation from PV **system**. These algorithms are widely used because of its low-cost and ease of realization. Proposed P&O and IncCon algorithms are implemented and tested under different loads, and the test results are analyzed and compared. The results show the performance of the IncCon algorithm in **tracking** MPP is better than the P&O algorithm and the experimental results of IncCon algorithm indicate that the feasibility and improved functionality of the **system** with has high-efficiency.

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The overall **system** block diagram consists of PV panel, charge controller, battery and inverter. The charge controller contains a DC-to-DC converter which matches the PV module voltage to battery voltage. Voltage and current sensors are present to sense the voltage and current and give them to microcontroller. The microcontrollers preprogramed to operate at **maximum** **power** **point** by using **perturb** and **observe** method. The data from the microcontroller can be transmitted to remote location through RS 485 interface. This helps in data logging and monitoring the data from a remote place. The overall block diagram is shown in Fig.2.

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ABSTRACT: The global demand for electrical energy is constantly increasing while the production of fossil fuel based energy is declining and therefore the obvious choice of clean energy source which is abundant and could provide security for the future development is sun’s energy. This paper presents the implementation of genetic algorithm (GA) based, **maximum** **power** **point** **tracking** (MPPT) for **photovoltaic** **system** (PV) under uniform and non-uniform irradiances. The **power** and voltage characteristic of PV array is non-linear and it exhibits multiple peaks including many local peaks and one global peak under non-uniform irradiances. In order to track the global peak, MPPT is the important component of PV systems. Then deduction of the required function to generate the reference values to drive the **tracking** **system** in the PV **system** at **maximum** **power** **point** (MPP) is done with the aid of Artificial Neural Network (ANN). This function deals with the more probable situations for variable values of temperature and irradiance to get the corresponding voltage and current at **maximum** **power**. The effectiveness of the proposed **system** is proved with the help of simulation. The simulation is performed in MATLAB/Simulink. From the simulation results, it shows that the proposed algorithm works properly to track the **maximum** **power** for PV **system** and to achieve high dynamic performance of the proposed **system**.

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ABSTRACT: At present, we are more concerned about the environmental issues caused by the consumption of conventional energy sources. That‟s why; we are focusing on the non-conventional energy sources like solar energy, wind energy, biomass energy, etc. to generate the required amount of electrical energy. Out of all the available energy resources solar energy is the most promising source of energy. But a **photovoltaic** **system** has two major drawbacks; the high installation cost and the low conversion efficiency of a PV **system**. To increase the efficiency of **photovoltaic** systems different types of MPPT techniques have been developed in past. In this paper we study and designed a PV **system** with incremental conductance (INC) based MPPT controller in SIMULINK. It also consists of a DC-DC converter. The implemented model extracts the **maximum** **power** from PV **system** and makes it available to the load hence it enhances the efficiency of the **system**.

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